Throughout a lifetime, bones and joints become damaged and worn through normal use and traumatic events. This degradation of the joints involving the articular cartilage and subchondral bone is known as arthritis and results in symptoms including joint pain, tenderness, stiffness, and potentially locking.
Joint replacement arthroplasty is an orthopedic procedure in which the arthritic surface of the joint is replaced with a prosthetic component. It is considered the primary form of treatment to relieve joint pain or dysfunction that may limit mobility. During an arthroplasty procedure, the ends of the bone and articular cartilage may be resurfaced or replaced.
The accurate placement and alignment of a prosthesis is a large factor in determining the success of a joint arthroplasty procedure. A slight misalignment may result in poor wear characteristics, reduced functionality, and a decreased longevity. To obtain accurate and durable implantation, one must not only achieve correct alignment of the prosthesis with the bone, but also correct positioning of the prosthesis within the bone to achieve reliable and durable anchoring.
In order to achieve these objectives, computer-assisted methods and systems have been developed that can provide three-dimensional models of the bone, models of the prosthesis, and model-in-model simulations. Based on these models and simulations, the methods and systems can generate three-dimensional models of a volume of bone to be removed in a computer-assisted surgical procedure, and guide the optimal positioning of these removed volumes within the bone. A cut-file with cutting parameters specifying a cut path to remove the volume of bone can then be generated, and can be used in computer-assisted surgery.
FIG. 1 illustrates a pathway according to commonly owned prior art technology (U.S. Pat. No. 5,824,085 to Sahay, A. et al.). There is a linear flow of steps, starting with the generation 001 of a bone model from a scanned image of a bone, the selection 002 of a prosthesis model from a library of prosthesis models, the generation 003 of a cavity model based on the prosthesis model, and the positioning 004 of the cavity model within the bone model.
Before the introduction of robot-assisted orthopedic surgery, the entire procedure, from planning to preparation to execution, was performed by the physician and their staff. The strength of this approach was an optimal use of the physician's personal skill and experience. However, the level of mechanical control was determined by the limitations of human skill and dexterity.
With the introduction of computer-assisted robotic surgery in the 1990s, the levels of mechanical control have greatly improved. Unfortunately, in part due to the boundaries of computer technology at the time, the scope of assistance that can be provided by the computer may be restricted to the execution of a cut file with cut parameters that are based on limited input, for instance input that is limited to the dimensions of a cutting cavity correlating to a particular prosthesis, and its position in a bone model. The use of one of the strengths of the pre-computer era, the physician's skill and experience, is reduced in favor of the mechanical control.
Examples of the consequences thereof are the fact that in the currently available technology a pre-existing set of cut files, based on the design of the prosthesis, may actually cause cutting interference with soft tissue, or may require cutting unnecessary areas using robotic assistance when the physician may prefer to cut certain regions without assistance.
Another example is the inability for the physicians to enter preferences based on personal experience, or based on patient-specific factors like age, life expectancy, body weight and expected physical activity.
Therefore, there is a need to improve patient outcomes by enabling more physician-specified input to be incorporated in the planning and execution of computer-assisted robotic surgery.